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Earthquake faults interact with each other in many different ways and hence earthquakes cannot be treated as individual independent events. Although earthquake interactions generally lead to a complex evolution of the crustal stress field, it does not necessarily mean that the earthquake occurrence becomes random and completely unpredictable. In particular, the interplay between earthquakes can rather explain the occurrence of pronounced characteristics such as periods of accelerated and depressed seismicity (seismic quiescence) as well as spatiotemporal earthquake clustering (swarms and aftershock sequences). Ignoring the time-dependence of the process by looking at time-averaged values – as largely done in standard procedures of seismic hazard assessment – can thus lead to erroneous estimations not only of the activity level of future earthquakes but also of their spatial distribution. Therefore, it exists an urgent need for applicable time-dependent models. In my work, I aimed at better understanding and characterization of the earthquake interactions in order to improve seismic hazard estimations. For this purpose, I studied seismicity patterns on spatial scales ranging from hydraulic fracture experiments (meter to kilometer) to fault system size (hundreds of kilometers), while the temporal scale of interest varied from the immediate aftershock activity (minutes to months) to seismic cycles (tens to thousands of years). My studies revealed a number of new characteristics of fluid-induced and stress-triggered earthquake clustering as well as precursory phenomena in earthquake cycles. Data analysis of earthquake and deformation data were accompanied by statistical and physics-based model simulations which allow a better understanding of the role of structural heterogeneities, stress changes, afterslip and fluid flow. Finally, new strategies and methods have been developed and tested which help to improve seismic hazard estimations by taking the time-dependence of the earthquake process appropriately into account.

In low-seismicity regions, such as France or Germany, the estimation of probabilistic seismic hazard must cope with the difficult identification of active faults and with the low amount of seismic data available. Since the probabilistic hazard method was initiated, most studies assume a Poissonian occurrence of earthquakes. Here we propose a method that enables the inclusion of time and space dependences between earthquakes into the probabilistic estimation of hazard. Combining the seismicity model Epidemic Type Aftershocks-Sequence (ETAS) with a Monte Carlo technique, aftershocks are naturally accounted for in the hazard determination. The method is applied to the Pyrenees region in Southern France. The impact on hazard of declustering and of the usual assumption that earthquakes occur according to a Poisson process is quantified, showing that aftershocks contribute on average less than 5 per cent to the probabilistic hazard, with an upper bound around 18 per cent

The statistics of time delays between successive earthquakes has recently been claimed to be universal and to show the existence of clustering beyond the duration of aftershock bursts. We demonstrate that these claims are unjustified. Stochastic simulations with Poissonian background activity and triggered Omori-type aftershock sequences are shown to reproduce the interevent-time distributions observed on different spatial and magnitude scales in California. Thus the empirical distribution can be explained without any additional long-term clustering. Furthermore, we find that the shape of the interevent-time distribution, which can be approximated by the gamma distribution, is determined by the percentage of main-shocks in the catalog. This percentage can be calculated by the mean and variance of the interevent times and varies between 5% and 90% for different regions in California. Our investigation of stochastic simulations indicates that the interevent-time distribution provides a nonparametric reconstruction of the mainshock magnitude-frequency distribution that is superior to standard declustering algorithm

Both aftershocks and geodetically measured postseismic displacements are important markers of the stress relaxation process following large earthquakes. Postseismic displacements can be related to creep-like relaxation in the vicinity of the coseismic rupture by means of inversion methods. However, the results of slip inversions are typically non-unique and subject to large uncertainties. Therefore, we explore the possibility to improve inversions by mechanical constraints. In particular, we take into account the physical understanding that postseismic deformation is stress-driven, and occurs in the coseismically stressed zone. We do joint inversions for coseismic and postseismic slip in a Bayesian framework in the case of the 2004 M6.0 Parkfield earthquake. We perform a number of inversions with different constraints, and calculate their statistical significance. According to information criteria, the best result is preferably related to a physically reasonable model constrained by the stress-condition (namely postseismic creep is driven by coseismic stress) and the condition that coseismic slip and large aftershocks are disjunct. This model explains 97% of the coseismic displacements and 91% of the postseismic displacements during day 1-5 following the Parkfield event, respectively. It indicates that the major postseismic deformation can be generally explained by a stress relaxation process for the Parkfield case. This result also indicates that the data to constrain the coseismic slip model could be enriched postseismically. For the 2004 Parkfield event, we additionally observe asymmetric relaxation process at the two sides of the fault, which can be explained by material contrast ratio across the fault of similar to 1.15 in seismic velocity.

Earthquake catalogs are probably the most informative data source about spatiotemporal seismicity evolution. The catalog quality in one of the most active seismogenic zones in the world, Japan, is excellent, although changes in quality arising, for example, from an evolving network are clearly present. Here, we seek the best estimate for the largest expected earthquake in a given future time interval from a combination of historic and instrumental earthquake catalogs. We extend the technique introduced by Zoller et al. (2013) to estimate the maximum magnitude in a time window of length T-f for earthquake catalogs with varying level of completeness. In particular, we consider the case in which two types of catalogs are available: a historic catalog and an instrumental catalog. This leads to competing interests with respect to the estimation of the two parameters from the Gutenberg-Richter law, the b-value and the event rate lambda above a given lower-magnitude threshold (the a-value). The b-value is estimated most precisely from the frequently occurring small earthquakes; however, the tendency of small events to cluster in aftershocks, swarms, etc. violates the assumption of a Poisson process that is used for the estimation of lambda. We suggest addressing conflict by estimating b solely from instrumental seismicity and using large magnitude events from historic catalogs for the earthquake rate estimation. Applying the method to Japan, there is a probability of about 20% that the maximum expected magnitude during any future time interval of length T-f = 30 years is m >= 9.0. Studies of different subregions in Japan indicates high probabilities for M 8 earthquakes along the Tohoku arc and relatively low probabilities in the Tokai, Tonankai, and Nankai region. Finally, for scenarios related to long-time horizons and high-confidence levels, the maximum expected magnitude will be around 10.

Reliable estimations of magnitude of completeness (M-c) are essential for a correct interpretation of seismic catalogues. The spatial distribution of M-c may be strongly variable and difficult to assess in mining environments, owing to the presence of galleries, cavities, fractured regions, porous media and different mineralogical bodies, as well as in consequence of inhomogeneous spatial distribution of the seismicity. We apply a 3-D modification of the probabilistic magnitude of completeness (PMC) method, which relies on the analysis of network detection capabilities. In our approach, the probability to detect an event depends on its magnitude, source receiver Euclidian distance and source receiver direction. The suggested method is proposed for study of the spatial distribution of the magnitude of completeness in a mining environment and here is applied to a 2-months acoustic emission (AE) data set recorded at the Morsleben salt mine, Germany. The dense seismic network and the large data set, which includes more than one million events, enable a detailed testing of the method. This method is proposed specifically for strongly heterogeneous media. Besides, it can also be used for specific network installations, with sensors with a sensitivity, dependent on the direction of the incoming wave (e.g. some piezoelectric sensors). In absence of strong heterogeneities, the standards PMC approach should be used. We show that the PMC estimations in mines strongly depend on the source receiver direction, and cannot be correctly accounted using a standard PMC approach. However, results can be improved, when adopting the proposed 3-D modification of the PMC method. Our analysis of one central horizontal and vertical section yields a magnitude of completeness of about M-c approximate to 1 (AE magnitude) at the centre of the network, which increases up to M-c approximate to 4 at further distances outside the network; the best detection performance is estimated for a NNE-SSE elongated region, which corresponds to the strike direction of the low-attenuating salt body. Our approach provides us with small-scale details about the capability of sensors to detect an earthquake, which can be linked to the presence of heterogeneities in specific directions. Reduced detection performance in presence of strong structural heterogeneities (cavities) is confirmed by synthetic waveform modelling in heterogeneous media.

We show how the maximum magnitude within a predefined future time horizon may be estimated from an earthquake catalog within the context of Gutenberg-Richter statistics. The aim is to carry out a rigorous uncertainty assessment, and calculate precise confidence intervals based on an imposed level of confidence a. In detail, we present a model for the estimation of the maximum magnitude to occur in a time interval T-f in the future, given a complete earthquake catalog for a time period T in the past and, if available, paleoseismic events. For this goal, we solely assume that earthquakes follow a stationary Poisson process in time with unknown productivity Lambda and obey the Gutenberg-Richter law in magnitude domain with unknown b-value. The random variables. and b are estimated by means of Bayes theorem with noninformative prior distributions. Results based on synthetic catalogs and on retrospective calculations of historic catalogs from the highly active area of Japan and the low-seismicity, but high-risk region lower Rhine embayment (LRE) in Germany indicate that the estimated magnitudes are close to the true values. Finally, we discuss whether the techniques can be extended to meet the safety requirements for critical facilities such as nuclear power plants. For this aim, the maximum magnitude for all times has to be considered. In agreement with earlier work, we find that this parameter is not a useful quantity from the viewpoint of statistical inference.

Due to large uncertainties and non-uniqueness in fault slip inversion, the investigation of stress coupling based on the direct comparison of independent slip inversions, for example, between the coseismic slip distribution and the interseismic slip deficit, may lead to ambiguous conclusions. In this study, we therefore adopt the stress-constrained joint inversion in the Bayesian approach of Wang et al., and implement the physical hypothesis of stress coupling as a prior. We test the hypothesis that interseismic locking is coupled with the coseismic rupture, and the early post-seismic deformation is a stress relaxation process in response to the coseismic stress perturbation. We characterize the role of stress coupling in the seismic cycle by evaluating the efficiency of the model to explain the available data. Taking the 2004 M6 Parkfield earthquake as a study case, we find that the stress coupling hypothesis is in agreement with the data. The coseismic rupture zone is found to be strongly locked during the interseismic phase and the post-seismic slip zone is indicated to be weakly creeping. The post-seismic deformation plays an important role to rebuild stress in the coseismic rupture zone. Based on our results for the stress accumulation during both inter- and post-seismic phase in the coseismic rupture zone, together with the coseismic stress drop, we estimate a recurrence time of M6 earthquake in Parkfield around 23-41 yr, suggesting that the duration of 38 yr between the two recent M6 events in Parkfield is not a surprise.

Various techniques are utilized by the seismological community, extractive industries, energy and geoengineering companies to identify earthquake nucleation processes in close proximity to engineering operation points. These operations may comprise fluid extraction or injections, artificial water reservoir impoundments, open pit and deep mining, deep geothermal power generations or carbon sequestration. In this letter to the editor, we outline several lines of investigation that we suggest to follow to address the discrimination problem between natural seismicity and seismic events induced or triggered by geoengineering activities. These suggestions have been developed by a group of experts during several meetings and workshops, and we feel that their publication as a summary report is helpful for the geoscientific community. Specific investigation procedures and discrimination approaches, on which our recommendations are based, are also published in this Special Issue (SI) of Journal of Seismology.

We study changes in effective stress (normal stress minus pore pressure) that occurred in the French Alps during the 2003-2004 Ubaye earthquake swarm. Two complementary data sets are used. First, a set of 974 relocated events allows us to finely characterize the shape of the seismogenic area and the spatial migration of seismicity during the crisis. Relocations are performed by a double-difference algorithm. We compute differences in travel times at stations both from absolute picking times and from cross-correlation delays of multiplets. The resulting catalog reveals a swarm alignment along a single planar structure striking N130 degrees E and dipping 80 degrees W. This relocated activity displays migration properties consistent with a triggering by a diffusive fluid overpressure front. This observation argues in favor of a deep-seated fluid circulation responsible for a significant part of the seismic activity in Ubaye. Second, we analyze time series of earthquake detections at a single seismological station located just above the swarm. This time series forms a dense chronicle of +16,000 events. We use it to estimate the history of effective stress changes during this sequence. For this purpose we model the rate of events by a stochastic epidemic-type aftershock sequence model with a nonstationary background seismic rate lambda(0)(t). This background rate is estimated in discrete time windows. Window lengths are determined optimally according to a new change-point method on the basis of the interevent times distribution. We propose that background events are triggered directly by a transient fluid circulation at depth. Then, using rate-and-state constitutive friction laws, we estimate changes in effective stress for the observed rate of background events. We assume that changes in effective stress occurred under constant shear stressing rate conditions. We finally obtain a maximum change in effective stress close to -8 MPa, which corresponds to a maximum fluid overpressure of about 8 MPa under constant normal stress conditions. This estimate is in good agreement with values obtained from numerical modeling of fluid flow at depth, or with direct measurements reported from fluid injection experiments.